Insights gained into activated sludge nitrification through structural and functional profiling of microbial community response to starvation stress. Issue 5 (14th March 2019) - Metch, Jacob W.
Abstract : An improved understanding of nitrifying microbial communities in wastewater treatment is imperative for proper design and operation of biological nutrient removal systems. Abstract : Although nitrification is widely applied for nitrogen removal in wastewater treatment plants (WWTPs), more information about the microorganisms involved and their corresponding capabilities and limitations is critical to refine kinetic parameters and process design to optimize advanced nutrient removal. Here we carried out a series of ammonia starvation stress experiments and applied a suite of assays to characterize the microbial community response. Illumina sequencing was applied to both DNA and RNA-derived ( i.e., cDNA) 16S rRNA amplicons to differentiate responses of functionally-active bacteria, with gene markers corresponding to known nitrifiers and compared to those targeted via quantitative polymerase chain reaction (qPCR). As expected, total bacterial DNA ( i.e., 16S rRNA genes) and nitrifier activity potential decayed over the course of the 18-day starvation period. Nitrospira was the only known nitrifying genera consistently detected via 16S rRNA amplicon sequencing in all samples. Despite relatively deep DNA sequencing (rarified to 38 000 sequences per sample), Nitrosomonas was the only other known nitrifying genera detected (4 of 84 samples), although Nitrobacter was detected via qPCR. Relative abundance of Nitrospira DNA and cDNA remained relatively constant throughout the starvation experiments and did not vary with temperature. Two Nitrospira OTUs were by far most dominant and were most closely related to known Nitrospira capable of mixotrophy and comammox. Thus, observed persistence of Nitrospira through starvation may be a function of diverse metabolic capability. Recognition that bacteria of diverse metabolic capability can drive nitrogen removal is critical to advance accurate modeling and design of advanced nutrient removal processes.